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Mastering flat_map in Python with List Comprehension

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Introduction In Python, when working with nested lists or iterables, one common challenge is flattening them into a single list while applying transformations. Many programming languages provide a built-in flatMap function, but Python does not have an explicit flat_map method. However, Python’s powerful list comprehensions offer an elegant way to achieve the same functionality. This article examines implementation behavior using Python’s list comprehensions and other methods. What is flat_map ? Functional programming  flatMap is a combination of map and flatten . It transforms the collection's element and flattens the resulting nested structure into a single sequence. For example, given a list of lists, flat_map applies a function to each sublist and returns a single flattened list. Example in a Functional Programming Language: List(List(1, 2), List(3, 4)).flatMap(x => x.map(_ * 2)) // Output: List(2, 4, 6, 8) Implementing flat_map in Python Using List Comprehension Python’...

6 Advantages of Columnar Databases over Traditional RDBMS

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In traditional RDBMS, when a data source is accessed by multi users at single time, then database will go into deadlock state. One of the advantages of a columnar model is that if two or more users want to use a different subset of columns, they do not have to lock out each other.         (Superior benefits for NoSQL Jobs) This design is made easier because of a disk storage method known as RAID (redundant array of independent disks, originally redundant array of inexpensive disks), which combines multiple disk drives into a logical unit. Data is stored in several patterns called levels that have different amounts of redundancy. The idea of the redundancy is that when one drive fails, the other drives can take over. When a replacement disk drive in put in the array, the data is replicated from the other disks in the array and the system is restored. The following are the various levels of RAID: RAID 0 (block-level striping without parity or mirroring) ...